Aoki, Yoshimitsu

写真a

Affiliation

Faculty of Science and Technology, Department of Electronics and Electrical Engineering (Yagami)

Position

Professor

Related Websites

Remarks

Professor

External Links

Profile Summary 【 Display / hide

  • ・1999年04月-2001年03月 早稲田大学理工学部 応用物理学科助手  橋本周司教授の研究室において、顔画像認識・合成、工業用精密画像計測、  ヒューマノイドロボットの視覚システムに関する研究に従事. ・2002年04月-2005年03月 芝浦工業大学工学部情報工学科 専任講師(青木研究室発足)  2005年04月-2008年3月 芝浦工業大学工学部情報工学科 准教授  顔形状・動作の3次元画像解析技術の医学・歯学応用  衛星画像他リモートセンシングデータの統合活用に関する研究  道路交通画像システム,高精度画像計測システムに関する研究等に従事.  ※芝浦工業大学にて、7年間で約90名の学生の研究指導を担当 ・2008年04月-現在 慶應義塾大学理工学部電子工学科 准教授  人物を対象とした画像計測・認識技術、及び応用システムに関する研究.  応用先として,セキュリティ,マーケティング,医療・福祉,美容,インターフェース,エンターテイメント,自動車,等を視野に入れ,幅広い産業応用を目指す.  人の認知機構や感性を考慮したメディア理解技術とその応用,新しい視覚センサ,ロバスト画像特徴量に関する研究等に従事. ・2013年2月-現在 株式会社イデアクエスト 取締役兼任  慶應理工発画像センシング技術の医療分野での実用化を目指している.

Career 【 Display / hide

  • 1999.04
    -
    2002.03

    早稲田大学, 理工学部 , 助手

  • 2002.04
    -
    2005.03

    芝浦工業大学 , 工学部 情報工学科, 専任講師

  • 2005.04
    -
    2008.03

    芝浦工業大学, 工学部 情報工学科, 助教授(2007より准教授)

  • 2008.04
    -
    2017.03

    慶應義塾大学, 理工学部, 准教授

  • 2013.02
    -
    2017.03

    株式会社イデアクエスト, 取締役

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Academic Background 【 Display / hide

  • 1996.03

    Waseda University, Faculty of Science and Engineering, 応用物理学科

    University, Graduated

  • 1998.03

    Waseda University, Graduate School, Division of Science and Engineering, 物理学及応用物理学専攻

    Graduate School, Completed, Master's course

  • 2001.02

    Waseda University, Graduate School, Division of Science and Engineering, 物理学及応用物理学専攻

    Graduate School, Completed, Doctoral course

Academic Degrees 【 Display / hide

  • 博士(工学), Waseda University, Coursework, 2001.02

 

Research Areas 【 Display / hide

  • Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Measurement engineering (Measurement Engineering)

  • Informatics / Database (Media Informatics/Data Base)

  • Informatics / Perceptual information processing (Perception Information Processing/Intelligent Robotics)

  • Life Science / Medical systems (Medical Systems)

 

Books 【 Display / hide

  • 顔の百科事典

    丸善出版, 2015.09

    Scope: 7 章 コンピュータと顔 ─顔の情報学─

     View Summary

    顔を見ない日はないというくらい、「顔」は私達にとってあたり前の存在ですが、私達は一体どれほど「顔」のことを知っているのでしょうか。そのような「顔」を総合的に研究するのが「顔学」です。 顔学には、動物学や人類学をはじめ、解剖学、生理学、歯学、心理学、社会学の文化的な対象として扱われるだけでなく、演劇や美術などの芸術学、コンピュータの分野では、情報学、さらに、美容学、人相学など、実に多様な学問分野と関係しています。 本書では、私達と切り離すことのできない「顔」の、歴史的・文化的・社会的・科学的側面を中項目の事典としてまとめられていることにより、多様な分野を横断する知識にも容易にアクセスが可能になっています。 日本顔学会創立20周年記念出版として、「顔学」について体系化を行った、初めての百科事典です。

  • 三次元画像センシングの新展開

    AOKI Yoshimitsu, NTS, 2015.05

    Scope: 第5章1節 色情報とレンジデータのフュージョンによる高分解能三次元レンジセンサの開発

  • 電気学会125年史

    AOKI Yoshimitsu, 電気学会, 2013.05

  • 電気学会125年史

    AOKI Yoshimitsu, 電気学会, 2013.05

  • マシンビジョン・画像検査のための画像処理入門

    AOKI Yoshimitsu, 日本工業出版, 2012.10

    Scope: pp.36-39

Papers 【 Display / hide

  • Non-Deep Active Learning for Deep Neural Networks

    Kawano Y., Nota Y., Mochizuki R., Aoki Y.

    Sensors (Sensors)  22 ( 14 )  2022.07

    ISSN  14248220

     View Summary

    One way to improve annotation efficiency is active learning. The goal of active learning is to select images from many unlabeled images, where labeling will improve the accuracy of the machine learning model the most. To select the most informative unlabeled images, conventional methods use deep neural networks with a large number of computation nodes and long computation time, but we propose a non-deep neural network method that does not require any additional training for unlabeled image selection. The proposed method trains a task model on labeled images, and then the model predicts unlabeled images. Based on this prediction, an uncertainty indicator is generated for each unlabeled image. Images with a high uncertainty index are considered to have a high information content, and are selected for annotation. Our proposed method is based on a very simple and powerful idea: select samples near the decision boundary of the model. Experimental results on multiple datasets show that the proposed method achieves higher accuracy than conventional active learning methods on multiple tasks and up to 14 times faster execution time from (Formula presented.) s to (Formula presented.) s. The proposed method outperforms the current SoTA method by 1% accuracy on CIFAR-10.

  • Event Collapse in Contrast Maximization Frameworks

    Shiba S., Aoki Y., Gallego G.

    Sensors (Sensors)  22 ( 14 )  2022.07

    ISSN  14248220

     View Summary

    Contrast maximization (CMax) is a framework that provides state-of-the-art results on several event-based computer vision tasks, such as ego-motion or optical flow estimation. However, it may suffer from a problem called event collapse, which is an undesired solution where events are warped into too few pixels. As prior works have largely ignored the issue or proposed workarounds, it is imperative to analyze this phenomenon in detail. Our work demonstrates event collapse in its simplest form and proposes collapse metrics by using first principles of space–time deformation based on differential geometry and physics. We experimentally show on publicly available datasets that the proposed metrics mitigate event collapse and do not harm well-posed warps. To the best of our knowledge, regularizers based on the proposed metrics are the only effective solution against event collapse in the experimental settings considered, compared with other methods. We hope that this work inspires further research to tackle more complex warp models.

  • Supporting collective physical activities by interactive floor projection in a special-needs school setting

    Oki M., Akizuki S., Bourreau B., Takahashi I., Aoki Y., Yamamoto J., Suzuki K.

    International Journal of Child-Computer Interaction (International Journal of Child-Computer Interaction)  32 2022.06

    ISSN  22128689

     View Summary

    This paper presents an algorithm to provide floor projection feedback according to the local distance and density of individuals. It is realized by a large-space floor projection system with a feedback function based on human tracking with laser ranging image sensors. The purpose is to support the cognition of spatial–temporal structures of groups of adolescents with neurodevelopmental disorders (NDs) that are conducting organized physical activity (PA). Observation and evaluation of behavioral changes in adolescents with NDs, when they were active with or without the floor projection based on the proposed algorithm, were conducted to validate its effectiveness. We observed that the proposed algorithm can be implemented in different organized PAs. It had the effect to help individuals in a behavior to keep a close distance to each other as a group rather than to keep the same distance apart from each other while walking.

  • Diverse Plausible 360-Degree Image Outpainting for Efficient 3DCG Background Creation

    Akimoto N., Matsuo Y., Aoki Y.

    Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition)  2022-June   11431 - 11440 2022

    ISSN  10636919

     View Summary

    We address the problem of generating a 360-degree image from a single image with a narrow field of view by estimating its surroundings. Previous methods suffered from overfitting to the training resolution and deterministic generation. This paper proposes a completion method using a transformer for scene modeling and novel methods to improve the properties of a 360-degree image on the output image. Specifically, we use CompletionNets with a transformer to perform diverse completions and Adjust-mentNet to match color, stitching, and resolution with an input image, enabling inference at any resolution. To improve the properties of a 360-degree image on an output image, we also propose WS-perceptual loss and circular inference. Thorough experiments show that our method out-performs state-of-the-art (SOTA) methods both qualitatively and quantitatively. For example, compared to SOTA methods, our method completes images 16 times larger in resolution and achieves 1.7 times lower Fréchet inception distance (FID). Furthermore, we propose a pipeline that uses the completion results for lighting and background of 3DCG scenes. Our plausible background completion enables perceptually natural results in the application of inserting virtual objects with specular surfaces.

  • Determinant analysis and developing evaluation indicators of grade of execution score of double axel jump in figure skating

    Hirosawa S., Watanabe M., Aoki Y.

    Journal of Sports Sciences (Journal of Sports Sciences)  40 ( 4 ) 470 - 481 2022

    ISSN  02640414

     View Summary

    A figure skating jump score is determined by the sum of the base value based on the difficulty and grade of execution (GOE) that indicates the performance quality. Therefore, performing a high-quality jump to obtain a high GOE is essential to win a competition. However, the relationship between the GOE and kinematic parameters remains unclear. We analysed the horizontal distance, vertical height, and landing speed of double axel jumps in the Ladies’ Short Program at the 2019 World Championships. The highest GOE group had significantly larger horizontal distances than the middle and lower groups, while the landing speed and vertical height were not significantly different. A principal component regression analysis was conducted to clarify the contrast between the three variables affecting the GOE. The results showed that greater horizontal distance and landing speed compared to vertical height (component 1) and greater horizontal distance compared to landing speed (component 3) contributed to higher GOE. We divided skaters into four clusters using these two components and provided general GOE acquisition strategies for each cluster. Finally, to apply our results to the industry, we proposed two new evaluation indicators which are highly correlated with the two components and easy to interpret.

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Papers, etc., Registered in KOARA 【 Display / hide

Reviews, Commentaries, etc. 【 Display / hide

  • 密集領域での動作を理解するためのハイブリッド型映像解析

    大内一成,小林大祐,中州俊信,青木義満

    東芝レビュー (東芝)  72 ( 4 ) 30 - 34 2017.09

    Internal/External technical report, pre-print, etc., Joint Work

  • 画像センシング技術によるチームスポーツ映像からのプレー解析

    林 昌希,青木 義満

    映像情報メディア学会誌 (映像情報メディア学会)  70 ( 5 ) 710 - 714 2016.09

    Article, review, commentary, editorial, etc. (scientific journal), Joint Work

  • Image Sensing Technologies and its Applications for Human Action Recognition

    AOKI Yoshimitsu

    Journal of JSNDI (日本非破壊検査協会)  65 ( 6 ) 254 - 260 2016.06

    Article, review, commentary, editorial, etc. (scientific journal), Single Work

  • パターン計測技術の深化と広がる産業応用 -総論-

    AOKI Yoshimitsu

    計測と制御 (SICE)  53 ( 7 ) 555 - 556 2014.07

    Article, review, commentary, editorial, etc. (scientific journal), Single Work

Presentations 【 Display / hide

  • 自由な表現と被写体の質感を維持するメイク生成モデルの開発

    帯金駿, 田川晴菜, 中川雄介, 中村理恵, 青木義満

    第27回日本顔学会大会(フォーラム顔学2022), 

    2022.09

    Oral presentation (general)

  • 不確実性を考慮したセマンティックマップの生成

    竹中悠,森巧磨,谷口恭弘,青木義満

    第27回 知能メカトロニクスワークショップ, 

    2022.09

    Oral presentation (general)

  • 重要パッチ選択に基づく効率的動画認識

    鈴木 智之, 青木 義満

    第25回 画像の認識・理解シンポジウム(MIRU2022), 

    2022.07

    Poster presentation

  • 音響信号を用いた人物の3次元姿勢推定

    川島穣, 柴田優斗, 五十川麻理子, 入江豪, 木村昭悟, 青木義満

    第25回 画像の認識・理解シンポジウム(MIRU2022), 

    2022.07

    Oral presentation (general)

  • 完全合成画像での学習による文書画像の影除去

    松尾祐飛,青木義満

    第28回画像センシングシンポジウム(SSII2022), 

    2022.06

    Poster presentation

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Intellectual Property Rights, etc. 【 Display / hide

  • 画像処理装置,画像処理プログラムおよび画像処理方法

    Date applied: 2019-105297  2019.06 

    Joint

  • 危険度推定装置,危険度推定方法及び危険度推定用コンピュータプログラム

    Date applied: 特願2015-005241  2015.01 

    Date issued: 特許第6418574号  2018.10

    Patent, Joint

Awards 【 Display / hide

  • HCGシンポジウム2018 特集テーマセッション賞

    秋月 秀一(慶大)・大木 美加・バティスト ブロー・鈴木 健嗣(筑波大)・青木 義満(慶大), 2018.12, 電子情報通信学会ヒューマンコミュニケーショングループ, 床面プロジェクションに伴う動的な環境変化に対応する人物追跡技術

    Type of Award: Award from Japanese society, conference, symposium, etc.

  • HCGシンポジウム2018 優秀インタラクティブ発表賞

    秋月 秀一(慶大)・大木 美加・バティスト ブロー・鈴木 健嗣(筑波大)・青木 義満(慶大), 2018.12, 電子情報通信学会ヒューマンコミュニケーショングループ, 床面プロジェクションに伴う動的な環境変化に対応する人物追跡技術

    Type of Award: Award from Japanese society, conference, symposium, etc.

  • 精密工学会沼田記念論文賞

    加藤直樹,箱崎浩平,里雄二,古山純子,田靡雅基,青木ヨシミツ, 2018.03, 精密工学会, 畳み込みニューラルネットワークによる距離学習を用いた動画像人物再同定

    Type of Award: Award from Japanese society, conference, symposium, etc.

  • IWAIT2018 Best Paper Award

    Ryunosuke Kurose, Masaki Hayashi, Yoshimitsu Aoki, 2018.01, IWAIT2018

    Type of Award: International academic award (Japan or overseas)

  • IES-KCIC2017 Best Paper Award

    Siti Nor Khuzaimah Amit, Yoshimitsu Aoki, 2017.09, IEEE Indonesia Section, Disaster Detection from Aerial Imagery with Convolutional Neural Network

    Type of Award: International academic award (Japan or overseas)

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Courses Taught 【 Display / hide

  • RECITATION IN ELECTRONICS AND INFORMATION ENGINEERING

    2022

  • LABORATORIES IN ELECTRONICS AND INFORMATION ENGINEERING(2)

    2022

  • INDEPENDENT STUDY ON INTEGRATED DESIGN ENGINEERING

    2022

  • IMAGING SCIENCE AND TECHNOLOGY

    2022

  • GRADUATE RESEARCH ON INTEGRATED DESIGN ENGINEERING 2

    2022

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Social Activities 【 Display / hide

  • 画像情報教育振興協会

    2013.07
    -
    2015.03
  • 独立行政法人 交通安全環境研究所

    2009.12
    -
    2012.03

Memberships in Academic Societies 【 Display / hide

  • International Symposium on Optomechatronic Technologies 2013, 

    2013.04
    -
    2013.11
  • International Workshop on Advanced Image Technology 2013(IWAIT2013), 

    2013.01
    -
    2013.09
  • 11th International Conference on Quality Control by Artificial Vision(QCAV2013), 

    2012.12
    -
    2013.05
  • 3rd International Conference on 3D Body Scanning Technologies, 

    2012.06
    -
    2012.10
  • 計測自動制御学会パターン計測部会, 

    2012.04
    -
    Present

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Committee Experiences 【 Display / hide

  • 2017.04
    -
    Present

    NEDO技術委員, NEDO

  • 2016.07
    -
    2016.11

    Optics & Photonics Japan 2016 推進委員, 日本光学会

  • 2016.07
    -
    2016.12

    Program committee member, International Workshop on Human Tracking and Behavior Analysis 2016

  • 2015.09
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    2016.08

    第22回画像センシングシンポジウム 実行委員長, 画像センシング技術研究会

  • 2014.09
    -
    2015.08

    第21回画像センシングシンポジウム 実行委員長, 画像センシング技術研究会

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